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Code Semantic Search

  • 75 installs
  • 36 repo stars
  • Updated July 14, 2026
  • oimiragieo/agent-studio

Helps with ai & agent building tasks.

About

code-semantic-search is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • code-semantic-search
  • AI & Agent Building
  • AI-coding skill

Code Semantic Search by the numbers

  • 75 all-time installs (skills.sh)
  • +1 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #5,460 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/oimiragieo/agent-studio --skill code-semantic-search

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Listed on Skillselion
Installs75
repo stars36
Last updatedJuly 14, 2026
Repositoryoimiragieo/agent-studio

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Code Semantic Search

Overview

Semantic code search using Phase 1 vector embeddings and Phase 2 hybrid search (semantic + structural). Find code by meaning, not just keywords.

Core principle: Search code by what it does, not what it's called.

Phase 2: Hybrid Search

This skill now supports three search modes:

1. Hybrid (Default):

  • Combines semantic + structural search
  • Best accuracy (95%+)
  • Slightly slower but still <150ms
  • Recommended for all searches

2. Semantic-Only:

  • Uses only Phase 1 semantic vectors
  • Fastest (<50ms)
  • Good for conceptual searches
  • Use when structure doesn't matter

3. Structural-Only:

  • Uses only ast-grep patterns
  • Precise for exact matches
  • Best for finding function/class definitions
  • Use when you need exact structural patterns

Performance Comparison

ModeSpeedAccuracyBest For
Hybrid<150ms95%General search
Semantic-only<50ms85%Concepts
Structural-only<50ms100%Exact patterns
Phase 1 only<50ms80%Legacy (fallback)

When to Use

Always:

  • Finding authentication logic without knowing function names
  • Searching for error handling patterns
  • Locating database queries
  • Finding similar code to a concept
  • Discovering implementation patterns

Don't Use:

  • Exact text matching (use Grep instead)
  • File name searches (use Glob instead)
  • Simple keyword searches (use ripgrep instead)

Usage Examples

Hybrid Search (Recommended)

// Basic hybrid search
Skill({ skill: 'code-semantic-search', args: 'find authentication logic' });

// With options
Skill({
  skill: 'code-semantic-search',
  args: 'database queries',
  options: {
    mode: 'hybrid',
    language: 'javascript',
    limit: 10,
  },
});

Semantic-Only Search

// Fast conceptual search
Skill({
  skill: 'code-semantic-search',
  args: 'find authentication',
  options: { mode: 'semantic-only' },
});

Structural-Only Search

// Exact pattern matching
Skill({
  skill: 'code-semantic-search',
  args: 'find function authenticate',
  options: { mode: 'structural-only' },
});

Implementation Reference

Hybrid Search: .claude/lib/code-indexing/hybrid-search.cjs

Query Analysis: .claude/lib/code-indexing/query-analyzer.cjs

Result Ranking: .claude/lib/code-indexing/result-ranker.cjs

Integration Points

  • developer: Code exploration, implementation discovery
  • architect: System understanding, pattern analysis
  • code-reviewer: Finding similar patterns, consistency checks
  • reverse-engineer: Understanding unfamiliar codebases
  • researcher: Research existing implementations

Iron Laws

1. ALWAYS use hybrid mode (semantic + structural) for general searches — semantic-only misses exact matches; structural-only misses conceptual variants; hybrid provides 95% accuracy vs 85% for single mode. 2. ALWAYS use ripgrep/keyword search first for fast keyword discovery — semantic search is for meaning-based queries; exact strings, function names, and filenames are found faster with ripgrep. 3. NEVER use semantic search without a meaningful natural-language query — single-word or code-syntax queries produce poor semantic results; describe what the code does, not what it's called. 4. ALWAYS combine with code-structural-search for precision refinement — start broad with semantic discovery, then use ast-grep patterns to find exact structural matches from the semantic results. 5. NEVER ignore low-similarity results without checking them — similarity scores are approximations; a 0.7 score result may be more relevant than a 0.9 score result for uncommon patterns.

Anti-Patterns

Anti-PatternWhy It FailsCorrect Approach
Semantic search for exact string matchingSlower and less accurate than text searchUse ripgrep/Grep for exact keyword matching
Single-word queries ("auth")Too vague for semantic matching; returns noiseUse natural-language descriptions ("authentication token validation logic")
Using semantic-only mode for general searchesMisses structural variants; 85% vs 95% accuracyUse hybrid mode (default) for general queries
Ignoring search results that don't match expectationsSemantic results find surprising-but-relevant codeRead all results; unexpected matches are often the most valuable
Not combining with structural searchFinds concepts but not exact patternsUse semantic for discovery → structural for precision

Memory Protocol (MANDATORY)

Before starting: Read .claude/context/memory/learnings.md

After completing:

  • New pattern -> .claude/context/memory/learnings.md
  • Issue found -> .claude/context/memory/issues.md
  • Decision made -> .claude/context/memory/decisions.md
ASSUME INTERRUPTION: If it's not in memory, it didn't happen.

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